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MCP MongoDB Server

MCP Server

LLM-powered interface to MongoDB with smart ObjectId handling

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Updated Dec 25, 2024

About

The MCP MongoDB Server lets large language models query, analyze, and modify MongoDB databases through a standardized protocol. It supports schema inspection, aggregation pipelines, read‑only safety, and intelligent ObjectId conversion.

Capabilities

Resources
Access data sources
Tools
Execute functions
Prompts
Pre-built templates
Sampling
AI model interactions

MCP MongoDB Server Demo | Claude Desktop

The Kiliczsh MCP Mongo Server is a Model Context Protocol (MCP) server that bridges large‑language models with MongoDB databases. By exposing a lightweight, read‑only interface, it allows AI assistants to discover the structure of collections and retrieve data without risking accidental writes or schema modifications. This solves a common pain point for developers who want to query databases through conversational agents while keeping strict security and audit controls in place.

At its core, the server presents each MongoDB collection as an MCP resource accessible via a URI. Each resource includes a human‑readable name, description, and an automatically inferred JSON schema that lists field names and data types. This schema information is invaluable for LLMs to understand the shape of the data, generate accurate queries, and provide meaningful summaries. Because the server runs with read‑only permissions, any query or aggregation executed through the MCP tools is guaranteed not to alter data, making it safe for production or sensitive environments.

Key capabilities include two query tools— and —which accept MongoDB query objects and return results in JSON format. The server also supplies prompts that generate descriptive text about a collection’s structure and basic statistics, enabling an AI assistant to explain schema details or data distributions without the user writing code. These prompts are especially useful in exploratory data analysis, onboarding new developers, or generating documentation automatically.

Developers can integrate the server into AI workflows by adding it to their Claude Desktop configuration or installing it via Smithery or . Once configured, the assistant can list available collections, request schema details, and run read‑only queries directly from a conversation. This tight integration streamlines data retrieval tasks, reduces context switching between IDEs and databases, and allows non‑technical stakeholders to interact with data through natural language.

Unique advantages of the Kiliczsh MCP Mongo Server include its strict read‑only enforcement, automatic schema inference that keeps LLMs up to date with evolving collections, and a simple JSON‑based prompt interface that turns raw database insights into readable summaries. These features make it an attractive choice for teams seeking secure, conversational access to MongoDB while maintaining the flexibility and power of MCP‑compliant AI assistants.